A New Coefficient of the Conjugate Gradient Method with the Sufficient Descent Condition and Global Convergence Properties

被引：0

作者：

Malik, Maulana ^{[1
,2
]}

Mamat, Mustafa ^{[1
]}

Abas, Siti Sabariah ^{[1
]}

Sulaiman, Ibrahim Mohammed ^{[1
]}

Sukono ^{[3
]}

机构：

[1] Univ Sultan Zainal Abidin, Fac Informat & Comp, Terengganu, Malaysia

[2] Univ Indonesia, Dept Math, Depok, Indonesia

[3] Univ Padjadjaran, Dept Math, Sumedang, Indonesia

来源：

ENGINEERING LETTERS | 2020年 / 28卷 / 03期

关键词：

Conjugate gradient method; unconstrained minimization problem; sufficient descent condition; global convergence; exact line search; strong Wolfe line search; NONLINEAR EQUATIONS; ALGORITHM;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Conjugate gradient methods are the most famous methods for solving unconstrained, large-scale optimization. In this article, we propose a new coefficient of the conjugate gradient method for solving unconstrained minimization problems. The new method is a modification of NPRP (2009) coefficient. The sufficient descent condition and global convergence of the new method are given under the exact line search and the strong Wolfe line search with sigma is an element of (0, 1/8). The numerical results show that the new method has good performance in solving unconstrained minimization problems.

引用

页码：704 / 714

页数：11

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